The magnitude of uncertainty in climate data that can blur the natural
climate variability varies greatly with various factors that introduce
biases. There are many factors that can impact the integrity of climate
observations. Factors such as data assurance and quality control and maintenance
are of great importance but are adequately covered under existing training
curriculum of NWS TC. In the interest of containing this tutorial to the
prescribed one hour session, we therefore focus our attention on the following:

Each factor is reviewed and then followed by recommended actions that
can be taken to either minimize or document potential impacts.

Our goal in climate monitoring is to measure variability and change in
natural environmental climate elements, not artificial ones such as those
introduced by changing instruments, relocating stations, observing practices,
etc.

Figure 5 illustrates our attempt to estimate of the relative importance
of various factors that can impact the integrity of temperature observations.
Other climate elements, such as precipitation (including snowfall), can
also be similarly impacted.

As you review the chart, you see that artificially induced biases/discontinuities
can be much greater in magnitude than the natural climate change/variability
signals we desire to measure and track. If unaccounted for, artificial
factors can totally overwhelm and blur the natural climate variability
and change signals we so carefully strive to monitor and potentially mitigate.